©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. This is a copyrighted publication of the IEEE. Further information and access can be found at http://www.ieee.org This version of the referenced work is the FINAL published version of the article; per allowable IEEE copyright policies, it is exactly the same as what is available at http://www.ieee.org The final published reference for this work is as follows: Paul Benjamin Lowry and Jay F. Nunamaker Jr. (2003). "Using Internet-Based, Distributed Collaborative Writing Tools to Improve Coordination and Group Awareness in Writing Teams," IEEE Transactions on Professional Communication (IEEETPC), vol. 46(4), pp. 277-297 (doi: 10.1109/tpc.2003.819650). If you have any questions and/or would like copies of other articles I’ve published, please email me at
[email protected], and I’d be happy to help. My vita can be found at http://marriottschool.byu.edu/employee/employee.cfm?emp=pbl
Electronic copy available at: http://ssrn.com/abstract=666125
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Using Internet-Based, Distributed Collaborative Writing Tools to Improve Coordination and Group Awareness in Writing Teams
—PAUL BENJAMIN LOWRY, MEMBER, IEEE,
AND JAY
F. NUNAMAKER, Jr.
Abstract—This paper argues for using specialized collaborative writing (CW) tools to improve the results of distributed, internet-based writing teams. The key features of collaborative tools that support enhanced coordination and group awareness are compared to existing writing tools. The first internet-based CW tool, Collaboratus, is introduced, and its group features are compared with those of Microsoft Word. Next, theoretical propositions, hypotheses, and constructs are formulated to predict outcomes of distributed groups that use CW tools. A four-week-long synchronous-distributed experiment then compares the outcomes of Collaboratus and Word groups. Innovative measures show that Collaboratus groups generally experience better outcomes than Word groups, in terms of productivity, document quality, relationships, and communication, but not in terms of satisfaction. The results buttress the conclusion that internet-based CW teams can benefit from specialized collaborative technologies that provide enhanced coordination, group awareness, and CW activity support. Index Terms—Collaborative writing (CW), distributed work, group awareness, group support systems, group writing, media richness theory.
Manuscript received September 2002; revised February 21, 2003. P. B. Lowry is with the Kevin Rollins Center for e-Business, Marriott School, Brigham Young University, Provo, UT 84602 USA (email:
[email protected]). J. F. Nunamaker, Jr. is with the Center for Management of Information, University of Arizona, Tucson, AZ 85721-0066 USA (email:
[email protected]). IEEE DOI 10.1109/TPC.2003.819640
B
uilding on face-to-face collaborative writing (CW), distributed CW is an increasingly important form of group work. Face-to-face CW is widely performed in industry, academia, and government [1]–[3]. As a pivotal form of professional communication, CW is useful for complicated writing projects that require more than one author [3]. Distributed, internet-based CW extends face-to-face CW into physically dispersed CW groups. Distributed CW is likely to continue to increase in practice because of the growing phenomenon of distributed work, driven by globalization and the internet.
Face-to-face CW is a complicated form of group work that becomes even more complicated in a distributed environment. Although face-to-face CW groups can produce more effective results than single authors for complicated writing projects, face-to-face CW is often performed suboptimally for several reasons [3]: (1) poor training or educational experiences with CW; (2) greater document complexity than single-author writing; (3) a wider range of emotions and perspectives than single-author writing; (4) difficulty in building consensus and a common understanding within a group; and (5) difficulty in predicting and measuring group success. Having physically
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dispersed group members only adds to the challenges of face-to-face CW. Distribution tends to decrease richness of interactions, increase group and social issues, and increase technological problems [4]–[6]. These additional challenges can lead to suboptimal results.
and causal empirical data; instead, such research tends to focus on nonempirical design discussions. The few empirical studies of CW tools tend to focus on measures of productivity, quality, and satisfaction—ignoring pivotal social measures such as communication and relationship quality. Less than 5% of CW research involves internet-based, distributed groups, and none of the previous CW tools have been designed for internet-based work. Despite recent advances in CW tool research, most distributed CW teams still use traditional word processing tools, combined with email. This practice suggests that a compelling case for using distributed CW tools has likely not been made. In summary, many research opportunities exist not only in developing internet-based CW tools, but also in providing theory, measures, and empirical data to better ascertain the value of such tools.
Several recent streams of research address how to better understand distributed CW and how to improve the results of distributed CW teams. Examples of studies that increase understanding of distributed CW include comparing face-to-face, asynchronous-distributed, and synchronous-distributed CW teams [7], comparing synchronous-distributed CW to face-to-face CW [8], and comparing asynchronous-distributed CW to face-to-face CW [5]. Examples of studies that address how to improve distributed CW results include a nonempirical discussion of how to better support distributed CW [9], a study on improving distributed CW in education [10], and a laboratory experiment showing how to increase process structure to improve asynchronous-distributed CW [11]. Moreover, several studies have investigated technologies to improve distributed CW: using basic webpages for distributed CW [12], improving asynchronous CW interfaces [13], using enhanced software designs for increased group awareness and coordination [14], and describing the evolutionary development of an internet-based CW tool [15]. Despite the progress of recent distributed CW research, research is needed to combine distributed CW tools with theory development and empirical results. An extensive review of 252 major CW research articles reveals that few of these articles involve CW tools in distributed settings [11]. Of this small group of distributed tool research, an even smaller subset uses theory building
Given the opportunities to further advance internet-based CW, this paper makes a theoretical and empirical case for using specialized distributed CW tools to improve the results of such groups. First, the key features of CW tools that support enhanced collaboration and communication are discussed and are then compared to word processors. Next, theoretical propositions, hypotheses, and constructs are proposed from collaboration literature to predict outcomes of distributed groups using CW tools versus groups using word processors. The first internet-based CW tool, Collaboratus, is then introduced, and its collaborative features are compared against those of Microsoft Word. The results of a four-week, synchronous-distributed experiment are used to compare Collaboratus versus Word groups, using an innovative array of perceived and observed communication measures. Finally, the results of the experiment are discussed in terms of their
contribution, limitations, and future research potential.
CASE FOR SPECIALIZED CW TOOLS This section presents the case for optimizing distributed CW group performance through using tools designed specifically for CW instead of word processors. First, the basic requirements to support collaboration are discussed; these requirements are then applied to word processors to explain why they are inadequate for CW. Next, requirements are discussed for supporting CW teams in distributed environments where word processors have even greater difficulty in supporting CW. The latest tool that supports internet-based, distributed CW is then presented, upon which further theory is built in the next section. Research regarding CW tools shows that software designed with specific collaborative features allows groups to better collaborate than groups using word processors. Several streams of CW tool research have established a baseline of required software features that will improve group coordination and group awareness, and enhance the specific activities of CW, as compiled in [11]. These key collaborative features are summarized below. Coordination is the ability of group members to co-manage their work efforts toward a common goal. Group awareness is the ability of group members to know what other group members are working on at any given time—an ability that improves understanding of context, coordination, and overall communication in collaborative activities [14]. Several CW tool features have been shown to enhance coordination, group awareness, and support of CW activities. CW tool research shows that effective CW tools should provide a shared group interface that allows different team members
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to work simultaneously in a coordinated fashion on different items of text without conflict or version-control problems [16]. Such an interface should include shared group documents [16], group annotations that allow simultaneous commenting on a given annotation [17], and hierarchical group outlines [16], [18]. CW tools also should provide features that support the various activities of CW, such as brainstorming, researching, planning, outlining, reviewing, revising, and final drafting [18], [19]. Finally, CW tools should support various CW roles [17]. The coordination and group awareness features of CW tools allow writing groups using CW tools to outperform groups using word processors. CW tools support parallel-partitioned writing, which is not supported by word processors [16]. Parallel-partitioned writing allows group members to work at the same time (synchronously) or at different times (asynchronously) on the same document, and provides separate document sections that each member can work on, yet allows each group member to be able to view or contribute to each other’s work at any time. Parallel-partitioned writing allows task decomposition, which has been shown to greatly increase coordination in collaborative groups [6]. Support of different roles and responsibilities also differentiates CW tools from word processors. CW tools should support multiple collaboration roles that can be easily shifted throughout the writing process [17]; such support also improves coordination and group awareness. Writing tools need to allow participants to easily create, join, or leave CW sessions at any time, without causing significant disruptions in CW processes [20]. The typical roles that should be provided include writer, consultant, editor, reviewer, scribe, and facilitator
[19], [21]. CW tools should provide capabilities and security that change dynamically according to a user’s role [19]. For example, by having roles and rights, nongroup members can be explicitly prohibited from document access, and group members can be given only the specific access they need for their work. Furthermore, roles facilitate better communication and coordination throughout the document-creation process. CW role support is increasingly important in industry, where writing tasks are rarely equally shared or co-authored. In industry settings, CW is more likely to take the form of multiple participants who provide input according to their experience, roles, and ability to commit time to a project [3]. In academia, however, writing projects are more likely to be co-authored, meaning participants share writing tasks equally, which is typically less efficient than using specific roles [3]. Not only should CW tools provide support for parallel-partitioned CW and dynamic roles, but also they need to support the key activities of group writing by providing interfaces for specific activities. For example, brainstorming can be supported by providing an interface that allows participants to add ideas anonymously but disallows participants from rushing ahead and writing document text. To support outlining, an interface can be provided that only allows writers (but not consultants or editors) to create a hierarchical outline without detailed text. To support reviewing, the writing interface could change by preventing writers from making changes, while editors are allowed to make annotations. By providing interfaces that are designed for specific CW activities, CW tools increase coordination by focusing group members on the specific tasks they are trying to accomplish. In contrast to CW tools, word processors do not have the
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essential features to support coordination, group awareness, and CW activities. Leading word processors, such as Microsoft Word 2002, do not provide shared group interfaces, shared group outlines, and annotations that support simultaneous editing. Worse, they do not support parallel-partitioned writing. Moreover, word processors lack basic support for various CW activities, such as brainstorming, researching, planning, and consensus building. Word processors do not provide writing interfaces that dynamically change to support group coordination on specific activities. In addition, word processors do not support the various roles of CW, and they require proprietary software that does not run through web browsers over the internet. Thus, little has changed since Kraut [22] concluded that word processors are inadequate for distributed CW efforts because word processors are highly specialized for layout and production of documents but not for high levels of group awareness in CW. Because word processors do not support pivotal coordination and group awareness features, confusion can easily reign in distributed groups that use word processors. Distributed group members using word processors can make changes at any time without the awareness of other group members. Likewise, word processors allow group members to rush prematurely into new CW activities before developing consensus with other group members. Group members also experience difficulty knowing what other group members are working on at any given time without using conferencing or emails. Lack of parallel-partitioned writing causes groups using word processors to choose CW strategies that require more time, require more coordination, and provide less group awareness. One typical approach in word processing groups is to simulate
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parallel-partitioned writing by having each group member work on a separate word processing document. This approach causes coordination and version-control problems because when group members work on separate documents in a distributed environment, it is difficult to know what other group members are working on at any given time. This can easily lead to duplicate work, separate agendas, frustration, and confusion.
and communication issues. For example, the second author can easily contradict the work of the first author, and the first author may not discover the discrepancies until the final draft is circulated. The three contrasting CW strategies are depicted in Fig. 1.
Other suboptimal approaches frequently chosen by groups that use word processors include single-scribe CW and sequential CW [16]. Single-scribe CW involves one person writing for an entire group, an arrangement that creates obvious limits on group involvement. Sequential CW involves one person writing at one time and then relinquishing control to another person when the writer is finished writing his/her portion. Such writing can result in coordination, productivity, Fig. 1.
Despite the coordination and group awareness features included in leading CW tools, such tools still have limitations in supporting distributed groups because they have not been designed for internet-based work. To support internet-based work, CW tools need to allow large groups, with little to no technical training, to work via web browsers that use virtually any type of computer and operating system. These requirements are critical because it is unreasonable to expect large, distributed groups to have the same type of computers and operating systems. It is also unreasonable to expect writers to install and troubleshoot their own
Depiction of the major CW strategies.
software—especially when they are working in different locations and time zones. Distributed CW environments naturally lack even more group awareness and coordination than face-to-face environments because teams in distributed environments are physically separated and have a restricted range of verbal and nonverbal cues [23].Yet, previous CW tools have been designed using technologies that are unable to work for distributed internet-based groups. Thus, internet-based writing groups often resort to more primitive, inefficient methods, such as file sharing through email, which have decreased the utility (and likely adoption) of CW tools. The current state of these tools creates an opportunity for specialized distributed CW tools. Because of the need for an internet-based CW tool, this study uses a new research tool designed to support distributed CW working over the internet. This tool, called Collaboratus, is the result of years
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of evolutionary field and laboratory research, as described in [15]. Collaboratus differentiates itself from previous tools because it is built entirely with the internet technology called Java. Java technology essentially allows Collaboratus to run through any internet web browser, operating system, and hardware platform, without end users needing to be aware of technical details. In fact, users can operate Collaboratus using the lowest-speed modem connections and still work effectively because this tool was designed to use communication over the internet. Collaboratus also supports virtually unlimited users, depending on the speed of the networks and the computers being used. Collaboratus builds on previous CW tools by supporting a full range of CW activities: setting up user roles and rights, creating group agendas and plans, sharing group outlines, voting on group decisions, creating group papers, reviewing and annotating, and brainstorming paper contents. Collaboratus also allows group members to work either asynchronously or synchronously in distributed work modes, or to use a mix of both. In summary, Collaboratus is a tool that meets the basic requirements of CW tools and supports teams in distributed, internet-based environments.
Table I compares several leading CW tools to Collaboratus. The next section builds the theoretical foundation necessary to test empirical outcomes of groups using Collaboratus versus groups using word processors.
PROPOSITIONS AND HYPOTHESES ON CW TOOLS This section builds a foundation for experimental research on distributed CW tools by creating testable hypotheses that compare Collaboratus groups versus Word groups. First, this section uses previous research to create general propositions on expected outcomes for users of CW tools. These propositions are generated for the constructs of productivity, quality, satisfaction, relationships, and communication. Second, because Collaboratus is an internet-based CW tool that is designed to replace word processors in distributed CW, specific differences in the group features provided by Collaboratus and Microsoft Word are highlighted. Third, these product-specific differences are combined with the theoretical propositions to create testable hypotheses. Propositions on Productivity CW tools increase productivity in CW groups, as measured in terms of TABLE I HIGHLIGHTS OF LEADING CW TOOLS
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time spent, idea production, and document lengths. Collaborative tool groups tend to spend less meeting time than noncollaborative tool groups that work on the same task [28]. They also spend less time managing meetings and clarifying communication [29]. Collaborative tool groups also commonly generate more unique comments than do face-to-face groups under the same time constraints, thus, showing a higher level of productive idea creation [30], [31]. Moreover, these groups produce significantly longer documents than do noncollaborative technology groups [32], a conclusion that has been confirmed by CW tool experiments [33]. Given these findings on productivity: P1: CW groups that use CW tools will experience higher productivity than similar groups using word processors. Propositions on Quality CW tools increase quality in CW groups, as measured by the external judgment of document quality and decision quality. Collaborative tool groups typically produce higher quality decisions [34] and results [35] than do noncollaborative tool groups, as judged by external experts. Likewise, groups using CW tools tend to generate higher quality documents than do non-CW tool groups, as judged
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by external judges [32], [33], [36]. Given these findings on quality:
Propositions on Relationships and Communication Groups using CW tools experience better relationships and communication (as measured by equality of participation, status differences, conformance, and conflict) than groups using word processors. Collaborative technology tends to foster equality in group decision making, group influence, and group participation—all of which positively impact the quality of group relationships. Collaborative technology diminishes dominance and conflict, and allows group members to express ideas more effectively [41], [42]. Collaborative technology can also reduce the effects of social context cues and perceived expertise; these reductions increase participation equality and decrease inhibition [43].
P2: CW groups that use CW tools will experience higher quality results than similar groups using word processors. Propositions on Satisfaction CW tools decrease outcome and process satisfaction in CW groups in the short term, as measured by respondent perceptions, but increase outcome and process satisfaction in the long term. In one-time experiments, noncollaborative tool groups tend to experience greater satisfaction and confidence than collaborative tool groups, as measured by respondent perceptions [35], [37]. Similarly, CW tool groups have also been shown to have lower satisfaction than word processing groups in one-time studies, even when CW tool groups had higher quality and longer documents [33]. The lower satisfaction often found in these groups can be partially explained by adoption and diffusion research, which predicts that new group technology can initially cause resistance and low satisfaction in groups, even if the new technology is clearly superior to the older, more familiar technology [38]. However, satisfaction with new collaborative technology increases over time with increased tool use and exposure [38]. This phenomenon is exhibited in a 13-week study on collaborative tool groups that shows satisfaction increasing over time [39]. A similar study shows that users who have worked with a collaborative system for a year have more satisfaction than face-to-face groups [40]. Given these findings on satisfaction: P3: CW groups that use CW tools on a one-time task will experience lower satisfaction than similar groups using word processors; CW groups that use CW tools on a task performed over time will experience higher satisfaction than similar groups using word processors.
In addition to fostering more equal participation, collaborative technology tends to reduce status differences, diminish conformance pressure, and decrease negative conflict. Collaborative technology has been shown to reduce status differences, which improves group relationships through equality in influence, participation, and communication [42], [44]. Yet the increased quality of communication and relationships from collaborative technology usually does not increase conformance—collaborative technology groups actually tend to have less conformance and agreement than traditional face-to-face groups [45]. Collaborative technology diminishes conformance pressure by creating an intermediary that abstracts group influence; thus, collaborative tool group members are less likely to change strongly held opinions than individuals in face-to-face groups [46]. Additional research demonstrates other relationship and communication benefits of collaborative tool use, such as less interpersonal conflict, better relationship development, and more constructive and productive conflict [47]. Given these findings:
P4: CW groups that use CW tools will experience better relationships and communication than similar groups using word processors. Hypotheses Applied to Collaboratus and Word in Distributed Settings Building on the previously constructed propositions, this section creates testable hypotheses to predict the outcomes of groups using Collaboratus versus groups using Word in distributed settings. This section first discusses specific features of Collaboratus that do not exist in Word and greatly alter coordination and group awareness. Additionally, the implications of using Collaboratus and Word in purely distributed settings are addressed. Finally, testable hypotheses are proposed. The key coordination and group awareness features that Collaboratus provides that are not supported by Word include support of parallel-partitioned work, support of the major CW activities, visual versioning, and support of various CW roles. Collaboratus is designed for parallel-partitioned work, which has been shown to greatly increase CW productivity [16]. Collaboratus groups are more likely to engage in productive, simultaneous work strategies and communication than those using Word because Word does not accommodate simultaneous group work without adversely affecting group awareness and coordination. Word tends to force groups to use sequential CW strategies, which lead groups down a path of lower productivity and more coordination, resulting in more redundancy, confusion, and communication problems. In addition to partitioned-parallel work, Collaboratus supports the major activities of CW, which improves group coordination. These activities are supported by providing various screens for different kinds of CW activities.
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Some of the key CW activities directly supported in Collaboratus that can be conducted by group members simultaneously include group brainstorming (Fig. 2), group voting (Fig. 3), group outlining (Fig. 4), group writing (Fig. 5), and group annotations that allow multiple levels of group discussions within a given annotation (Fig. 6). Having different screens and features, according to the activity a group is working on, greatly increases coordination by focusing team members on the appropriate task at hand. Word does not provide shared brainstorming and group voting, and only provides partial support for group outlining, group writing, and group annotations. Collaboratus also has other features that improve group awareness and coordination. Collaboratus has a version-control feature that allows participants to Fig. 2.
Collaboratus brainstorming.
visualize the changes that have been made to a particular section of a document. It also supports specific CW roles and the ability to verify who is actively working on a CW document at any given time. Word provides no security or support for writing roles, and only has partial support for visual version control. Table II lists specific coordination and group awareness features, and shows the extent to which Word supports them. Collaboratus groups should not only have better results than Word groups in face-to-face interactions, but they should also have better results in distributed interactions. The media richness theory predicts that distributed work groups will exhibit media interactions that are less rich than interactions in face-to-face groups, and this lack of richness decreases the quality of communication and overall outcomes of distributed
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groups [48]. However, software designed with group-oriented interfaces improves the richness of interactions in distributed groups, and thus increases the quality of communication and overall outcomes [5], [48]. Thus, the coordination and group awareness features that have been added to Collaboratus provide more media richness advantages than Word provides. For example, by seeing a shared outline, Collaboratus users will have fewer questions regarding who is doing what and when and, thus, will have fewer coordination and redundancy problems. Collaboratus users will likely identify issues and build off of each other’s work more rapidly because they can see the work of others in parallel. In support of the media richness theory, research also indicates that communication support through technology features is crucial in distributed collaborative
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groups [23]. Distributed groups tend to need communication on two levels: (1) the data level, where information is exchanged and (2) the relationship level, where activities are coordinated (see Fig. 7). Thus, the lack of group awareness and coordination features in Word severely undermines its efficacy for distributed CW because it does not adequately support relationship-level communication and does not provide a rich, collaborative media. In contrast, Collaboratus supports distributed CW much more effectively than does Word because Collaboratus allows distributed groups to work over the internet on virtually any web browser and computer platform, whereas Word does not. In summary, combining specific CW-feature differences between Collaboratus and Word with propositions 1–4 yields the following testable hypotheses. Fig. 3.
Collaboratus voting.
H1: Distributed CW groups that use Collaboratus will experience higher productivity than similar groups that use Word. H2: Distributed CW groups that use Collaboratus will experience higher quality documents than similar groups that use Word. H3: Distributed CW groups that use Collaboratus over time will experience higher satisfaction than similar groups that use Word. H4: Distributed CW groups that use Collaboratus will experience better relationships than similar groups that use Word. H5: Distributed CW groups that use Collaboratus will experience better communication than similar groups that use Word.
METHOD This section describes the experimental method used to test the study’s hypotheses. The
research method is described in terms of its design, participants, measures, and procedures. The design for this experiment involved control groups using Word 2000 with NetMeeting and treatment groups using Collaboratus with NetMeeting; both treatment and control groups worked in synchronous-distributed work modes. Treatment and control groups used NetMeeting for all communication because Word lacks communication capabilities (e.g., discussion tools); thus, tool comparisons were able to better isolate group awareness and coordination differences between the tools. Subjects for this experiment volunteered for graded class credit from an undergraduate MIS class at a large, southwestern university. Initially, 66 subjects agreed to participate, but only 47 students fully participated (males n = 21, females n = 18,
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no report = 8; average age is 20.79 years, SD = 3:1).
Several measures were used to capture the underlying constructs of productivity, quality, satisfaction, relationships, and communication. These measures were designed to capture their underlying theoretical meanings as closely as possible, using multiple measurement approaches: (1) perceived measures were extracted from multiple-item scales in the post-experiment survey; (2) observed measures were extracted from the group papers; (3) judged measures were obtained by having external judges independently evaluate document quality; (4) chat logs of all groups were coded and analyzed by external judges to capture communication and relationship measures. Full chat transcripts for all groups were captured electronically from NetMeeting and coded by external judges for different observed message types representing communication and relationship Fig. 4.
Collaboratus group outlining.
constructs. The chat logs were analyzed for the key CW sessions (sessions 3 and 4) and were broken up into distinct fragments consisting of a subject–verb (thought unit). Because a given message can be deconstructed into several, disparate subject–verb fragments, the categories were assigned in a mutually exclusive fashion. All coding values were nominally rated by the judges—no attempt was made to assess the degree to which a category applied. The specific measures used for all four approaches are described in terms of productivity, quality, satisfaction, relationships, and communication. Three measures of perceived and observed productivity were used in this experiment: observed length (the total number of words produced in a document), perceived participation (six items, = 0:77), and observed participation in chat sessions (the number of words contributed by a group’s members). Observed
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participation was the primary measure of involvement because it measures how engaged group members are with each other regardless of the dominance and/or affiliation that is taking place [49]. Quality was assessed by the participants and by external judges. These measures included perceived quality of the document (eight items, = 0:89) and externally judged quality. Externally judged quality of the groups’ documents was assessed by five external judges, using procedures similar to paper judgment approaches used by [50] and [33] (five items interrater reliability of 0.77). Satisfaction was assessed through perceived measures and through chat-log analysis. Perceived satisfaction measures include: satisfaction (four items, = 0:87) from the posttest survey, in CW enjoyment from the experiment (three items pretest, = 0:70,
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three items posttest, = 0:84), and expressions of confusion and dissatisfaction as found in chat logs (session three, = 0:96, session four, = 0:79). Relationship and communication measures were collected through perceived measures and from external analysis of the groups’ chat logs. The perceived measures include perceived agreement (11 items, = 0:89), perceived strength of interpersonal relationships (two items, = 0:91), and perceived respect (two items, = 0:73). Perceived strength of personal relationships is further enhanced by a posttest measure that asks participants to rate how well they knew team members before and after the project. Simultaneous work is assessed by asking participants the degree to which they believe their group worked at the same time. Observed consensus was gathered by two methods. First, groups were measured on the percentage of Fig. 5.
Collaboratus group writing.
chat participation by each group member because consensus is positively related to higher levels of involvement of team members. Second, chat logs were coded for agreement. Several measures were also derived directly by external analysis of the groups’ chat logs: coordination (session three, = 0:99, session four, = 0:97), agreement/consensus (agreement positive, session three, = 0:95; agreement negative, session three, = 0:96; agreement positive, session four, = 0:82; agreement negative, session four, = 0:98), positive affiliation (session three, = 0:98, session four, = 0:88), and socialization (session three, = 0:95, session four, = 0:99). Turning from the measures, several procedures were carefully followed to increase experimental control and realism. First, the writing environment was strictly controlled for both treatment and control groups. Each group participated in four separate
sessions of the laboratory experiment. Both treatment and control groups met at exactly the same time, but in separate collaborative tool rooms, located in two different buildings. Both rooms were of similar layout, equipment, and size. All sessions took place during class time, lasted approximately one hour, and were completed several days apart during a period of one month. Subjects were randomly assigned to groups of three and required to sit at workstations apart from their team members. They could not speak orally, and could only communicate using NetMeeting’s chat feature. To further improve experimental control, the sessions were carefully scripted. Trained experiment facilitators read from pretested scripts to ensure that all of the participants conducted the major activities of CW (team formation, brainstorming, outlining, drafting, reviewing, revising, and final
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drafting) in the same way. Teams could not create their own CW activities and processes, and were strictly monitored to ensure they followed the scripted facilitation. The facilitators also carefully timed each activity so that both treatment and control groups spent the same amount of time on each of the activities.
RESULTS OF ANALYSIS Given the strong experimental controls, stringent procedures, and rich array of measures, this experiment produced several significant results. In summary: H1: Distributed CW groups that use Collaboratus will Fig. 6.
Group annotations.
experience higher productivity was supported in two of the three productivity measures. H2: Distributed CW groups that use Collaboratus will experience higher quality was supported by externally measured quality, but not in terms of perceived quality. H3: Distributed CW groups that use Collaboratus will experience higher satisfaction was not statistically supported by the satisfaction measures, although the differences were in the predicted direction. H4: Distributed CW groups that use Collaboratus will experience
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better relationships was partially supported in terms of observed socialization, positive support, and negative support. H5: Distributed CW groups that use Collaboratus will experience better communication was supported in terms of use of simultaneous communication, but not in terms of coordination. These results are summarized in Table III.
DISCUSSION OF RESULTS Given the statistical results of the experiment, it can be concluded that the key features in Collaboratus that promote
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coordination and group awareness provided advantages to the Collaboratus groups.
increased document length and quality.
In terms of significant results, Collaboratus groups were generally more productive than Word groups. Collaboratus groups produced lengthier documents than Word groups and had much lengthier chat discussions during final drafting (session 4), although there was no difference exhibited during drafting and reviewing (session 3), as seen in Fig. 8. There is also a strong correlation between
Collaboratus groups produced higher quality documents than Word groups, according to external judges, but not in terms of perceived quality, although the perceived results were in the predicted direction. This apparent contradiction highlights potential weaknesses of perceived document quality measures reported by participants and emphasizes the need for external writing experts to judge
quality. The external judges were likely much more objective and accurate than the participants because the judges were blind to the experiment condition represented by a given paper, and they had more writing expertise than the participants. In contrast, the participants’ perceptions of their own writing quality were similar between control and treatment groups, perhaps because of the participants’ lack of expertise and/or their inability to rate themselves objectively. Word groups may also have been
TABLE II COLLABORATUS CW FEATURES VERSUS WORD
Fig. 7.
Data- and relationship-level collaborative work communication needs.
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oblivious to their poor writing quality because of a lack of coordination and group awareness. Finally, the groups that had the highest judged quality also had the highest document lengths, in support of similar conclusions by [51].
No differences appeared between Collaboratus groups and Word
groups in terms of perceived and observed satisfaction; however, perceived satisfaction differences did appear in the predicted direction. Not only were the perceived measures insignificant, but also the coded measures of confusion and dissatisfaction messages from chat logs of sessions 3 and 4 did not yield significant results, although the results were in the predicted
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direction. These results are somewhat paradoxical because the Collaboratus groups were more productive, had better quality, and generally had better relationships and communication. Perhaps four sessions of the experiment were insufficient for Collaboratus groups to develop comfort with Collaboratus, and this lack of comfort diminished their satisfaction.
TABLE III RESULTS OF HYPOTHESIS TESTING IN THIS EXPERIMENT
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In terms of relationships and communication, several mixed results occurred. The two measures of perceived relationships were not significant, but they were in the predicted direction. Perceived respect was not significant and was not in the predicted direction. Moreover, there were no statistical differences in observed coordination messages between groups in either session, although both sessions were in the predicted direction in that Word groups required more coordination messages. One explanation for this is that Word groups appeared to conduct more rudimentary coordination (e.g., “where is the section on. . .?”) whereas Collaboratus groups performed more advanced coordination (e.g., “I like your discussion on. . .but I think if you combine it with. . .in consideration of. . .that we will be more persuasive.”). Thus, although the number of coordination messages was similar, the quality of coordination messages was higher for Collaboratus groups.
However, chat-log analysis of socialization showed Collaboratus groups acting more social than Word groups in the final session. Interestingly, during session three (drafting and revising), there was no significant difference in socialization levels. This suggests that both groups were busy with the task at hand, especially given the low socialization scores of 2.0 for Word groups and 1.2 for Collaboratus groups. However, in session four (final drafting), there were vast differences between the groups: Word groups received a score of 1.3 and Collaboratus groups received a score of 23.8. This likely accounts for some of the chat length differences (see Fig. 8 and 9). It appears that although the treatment and control groups had the same amount of time for each session, the Collaboratus groups reached their objectives sooner (because of higher productivity) and, thus, spent more time socializing and bonding toward the end of the last session. Meanwhile, Word groups tended to work frantically and were less social throughout the entire session.
Fig. 8. Chat length differences from session 3 to session 4.
Collaboratus groups also had stronger manifestations of both negative and positive support than did Word groups. There were great statistical differences in session three in terms of negative and positive support—Collaboratus groups led in both areas. Collaboratus groups possibly experienced more negative and positive messages in the same session because the richness and variety of their conversations about work were higher (as a result of enhanced coordination and group awareness). Such patterns are observed in constructive conflict when people are objectively trying to resolve differences toward a common goal. Interestingly, the Word groups had no measured levels of negative conflict in drafting and reviewing, yet they manifested several positive messages. This pattern suggests conformance because negative and contradictory messages were not observed, and this absence tends to result in suboptimal outcomes. The lower quality associated with conformance was also supported by the judged quality results.
LOWRY AND NUNAMAKER: USING INTERNET-BASED, DISTRIBUTED CW TOOLS
In addition to finding significant differences in CW group interactions, this study also makes useful contributions in the areas of theory building, measures, and methodology for CW tool research. This study continues to build a base of theory that can be used to predict outcomes of distributed CW tool groups. Measurement of CW group outcomes is advanced by using multidimensional measures of productivity, quality, satisfaction, communication, and relationships. Measures include not only typical approaches of gathering participant perceptions but also directly observable measures, measures using external judges to analyze chat logs, and measures using external judges to rate document quality. These measures allow additional insights into the communication and relationship aspects of CW that have not been addressed in most CW tool studies. Great differences are evident in group outcomes, depending on the level coordination, group awareness support, and CW activities support in the chosen CW tool. Fig. 9.
The validity of these measures is enhanced by an innovative controlled laboratory environment in which control and treatment groups write over a series of several weeks. This design provides high levels of control and the ability to focus on the group awareness and coordination differences between the software packages. Additionally, the design provides enhanced realism. In contrast, most previous CW tool experiments have taken place in one-time settings that do not reflect the complexity and time dimensions of most CW.
LIMITATIONS Despite the contributions of this study, limitations still exist that need to be addressed. Although the laboratory setting was more realistic than most settings, since it took place over time, the tightly controlled environment still affected realism and generalizability to other settings and tasks. Specifically, the environment involved small teams of students working on an academic task of moderate
Socialization differences from session 3 to session 4.
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complexity. Although academic CW is a legitimate and substantial domain of inquiry, the results may not be generalizable to other settings and tasks, such as CW in a professional setting. Research indicates that distinct differences exist between the way CW is performed in academia and industry [3]. A key difference is that nonproductive (time intensive) approaches to CW in academia are generally acceptable because even nonproductive approaches often benefit learning and socialization; whereas in industry, productivity (in terms of time on task) is a much more significant driver of collaboration. Thus, industry participants tend to play different CW roles, do not share equally the writing task, and tend to choose co-authoring only when absolutely necessary [3]. Likewise, participants in industry are much more likely to play distinctly defined CW roles according to expertise and time commitments, as opposed to more democratic divisions of work that are seen in academia. On the other hand, the significant productivity results in this experiment may be all
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the more significant in industry settings.
problems cannot be discussed and addressed immediately. Thus, the lack of support for CW activities, coordination, and group awareness in word processors is likely to undermine asynchronous-distributed CW groups, whereas Collaboratus would likely provide enhanced results for such groups.
Likewise, the experiment’s writing task does not necessarily apply directly to CW tasks that either require different group processes or have outcomes evaluated with different priorities. For example, the findings may not generalize well to a high-status military environment where participants are working on a highly political policy proposal, where status differences are likely to remain strong, and where equal participation may not be highly valued. In creative group writing, group members may place little value on productivity but highly value creativity. Examples of other types of CW that likely have unique processes and outcome weightings include production of corporate strategy documents, proposals, and academic journal articles. The use of synchronousdistributed work groups also creates unique dynamics in the laboratory setting that may limit the generalizability of the findings to synchronous-distributed work. Although synchronous-distributed writing is conducted quite often in practice, it is probably less prevalent as asynchronous-distributed CW, especially among groups working over the internet. Synchronous work was chosen for purposes of control, whereas asynchronous work is difficult to control in laboratory settings. Regardless, the results of this experiment likely generalize to asynchronous environments because such environments lack even more coordination and group awareness, since asynchronous-distributed participants typically do not work synchronously or do so only sporadically. Asynchronous groups still have the same basic needs for group awareness and coordination. Delays in updates and lack of group awareness can cause even more issues in asynchronous teams because
Moreover, control and treatment groups had different levels of exposure to Collaboratus and Word, and this may have significantly diminished statistical differences. Virtually all participants had several months or several years of experience using Word, whereas participants in the Collaboratus treatment had only several hours of exposure to Collaboratus. Thus, significant gaps in learning curves and experience likely depressed statistical differences between treatment and control groups. This only highlights the significance of the empirical findings—if students had more comfort and experience with Collaboratus, the results may have been even more positive, especially in terms of satisfaction due to adoption/diffusion. Three other differences between treatment and control groups, due to the selected tools, need to be clarified. First, Word is a professional product that has undergone thousands of hours of usability testing and reengineering, whereas Collaboratus is a noncommercial research product that has had limited usability testing. Like the differences in tool exposure, this limitation emphasizes the significance of the findings. Second, the experimental results directly apply only to the Year 2000 version of Word, not to Word 2002, although similar outcomes would likely occur with Word 2002. Since the experiment was conducted, Microsoft Office 2002 has added some group features that merit future experiments. Probably the
most useful improvement is the introduction of online meetings in NetMeeting, which now allows the use of a shared Word document. The combination of these products allows semishared outlining, but does not fully meet the requirements for CW tools because only one person can edit the document at a time (although all participants can see a document’s changes on their screens). Word 2002 still does not support a shared group outline, with section locking and simultaneous writing. Overall, Word 2002 would likely produce negative distributed CW results similar to those of the Word 2000 groups in this experiment. Third, a key simplifying assumption is that this study follows the norms of other collaborative tool research in comparing bundles of features against each other. Hence, the group awareness, coordination, and CW features of Collaboratus were compared as a whole to all the group features in Word for the same CW activities and the same task. Thus, it is impossible from this empirical data to infer that the group outliner in Collaboratus is responsible for x% of the outcome differences, while the group annotation feature is responsible for y% of the outcomes differences, and so forth. Determining which exact feature accounts for what percent of a particular measure is not possible. This would require a massive number of participants using many different versions of Collaboratus that have every possible permutation of group awareness and coordination features turned on and off (e.g., a version without a group outliner, a version without group annotations, and so forth). Further complicating such an approach is that the group awareness and coordination features of Collaboratus are designed to be used in concert with each other; thus, a version of Collaboratus that did not have the group outliner would undermine virtually every other group awareness and coordination feature.
LOWRY AND NUNAMAKER: USING INTERNET-BASED, DISTRIBUTED CW TOOLS
FUTURE RESEARCH The significant contributions and limitations of this study open up a wide variety of future research possibilities. In terms of methodologies, future research should include the use of industry professionals in field settings as well as asynchronous-distributed CW field experiments. It would also be useful to further establish empirically the superiority of parallel-partitioned work by comparing sequential CW groups to parallel-partitioned CW groups. Research can also be conducted to prioritize measures, depending on the type of CW task being conducted. More studies that use longitudinal measures and chat logs can be conducted to provide richer measures. This study also inspired several future CW tool design ideas, which represent interesting ways to implement software enhancements
for CW tools and new lines of future communication and collaboration research. Some of the future design considerations for CW tools that would most likely enhance coordination and group awareness are summarized in Table IV. As CW tools improve through integration with these ideas, the lines will be blurred between CW tools and knowledge-management tools, creating significant synergies for group work. For example, existing document-management tools are adept at sequential coordination but do not provide simultaneous editing on a shared group outline and lack other group awareness features found in CW tools. As these tools merge, the capabilities and utility of such tools will greatly improve.
CLOSING REMARKS This study makes the case that specialized CW tools can
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improve results of distributed CW groups. Because the groups in this experiment worked in a highly controlled environment (used the same conditions on the same scripted task, and used the same communication technology), this experiment was able to reasonably isolate the effects of the coordination and group awareness differences between Collaboratus and Word. Collaboratus had specific features that provided better coordination and group awareness, such as its shared outlines, support of simultaneous work, visual versioning, support of roles, and section locking. These features altered dramatically the socialization and collaboration in CW groups, and brought related benefits such as increased productivity and quality. The results support the conclusion that internet-based CW teams can benefit from specialized collaborative technologies that
TABLE IV SUMMARY OF KEY FUTURE DESIGN CONSIDERATIONS FOR CW TOOLS
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provide enhanced coordination, group awareness, and CW activity support. Likewise, the use of word processors as the primary tool of distributed CW groups will continue to lead to suboptimal results.
Mark Adkins, John Kruse, and Jim Lee, all from the Center of the Management of Information (CMI) at the University of Arizona. We also greatly appreciate the development work conducted by Conan Albrecht, Abhiraj Jadhav, Ankur Jain, and Hemanth Manda. We also acknowledge the support and funding we have received from DESCIM (Defense
ACKNOWLEDGMENT We appreciate contributions made by Queen Esther Booker,
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Paul Benjamin Lowry (M’99) is an Assistant Professor of IS at the Marriott School of Management, Brigham Young University, and a Faculty Researcher at the Kevin and Deborah Rollins Center for e-Business. His interests include internet-based collaboration, virtual teams, distributed facilitation, collaborative software, e-Business, group-based HCI, heuristics, and scientometrics. Dr. Lowry received his Ph.D. in MIS from the University of Arizona, and a B.S. in Information Management and an MBA, both from Brigham Young University.
Jay F. Nunamaker, Jr. is Regents Professor and Director of CMI at the University of Arizona. He has published scores of articles and has received many awards, including the DPMA EDSIG Distinguished IS Educator Award, the Groupware achievement award, and the Andersen Consulting Professor of the Year award. The GroupSystems software resulting from his research has been implemented in hundreds of organizations. Jay received his Ph.D. in systems engineering and operations research from Case Institute of Technology, a M.S. and B.S. from the University of Pittsburgh, and a B.S. from Carnegie Mellon University.
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